BUG: dropna() on single column timezone-aware values (pandas-dev#13407)

Author: JQGoh

doc/source/whatsnew/v0.23.0.txt

@@ -902,11 +902,12 @@ Timezones
 - :func:`Timestamp.replace` will now handle Daylight Savings transitions gracefully (:issue:`18319`)
 - Bug in tz-aware :class:`DatetimeIndex` where addition/subtraction with a :class:`TimedeltaIndex` or array with ``dtype='timedelta64[ns]'`` was incorrect (:issue:`17558`)
 - Bug in :func:`DatetimeIndex.insert` where inserting ``NaT`` into a timezone-aware index incorrectly raised (:issue:`16357`)
-- Bug in the :class:`DataFrame` constructor, where tz-aware Datetimeindex and a given column name will result in an empty ``DataFrame`` (:issue:`19157`)
+- Bug in :class:`DataFrame` constructor, where tz-aware Datetimeindex and a given column name will result in an empty ``DataFrame`` (:issue:`19157`)
 - Bug in :func:`Timestamp.tz_localize` where localizing a timestamp near the minimum or maximum valid values could overflow and return a timestamp with an incorrect nanosecond value (:issue:`12677`)
 - Bug when iterating over :class:`DatetimeIndex` that was localized with fixed timezone offset that rounded nanosecond precision to microseconds (:issue:`19603`)
 - Bug in :func:`DataFrame.diff` that raised an ``IndexError`` with tz-aware values (:issue:`18578`)
 - Bug in :func:`melt` that converted tz-aware dtypes to tz-naive (:issue:`15785`)
+- Bug in :func:`Dataframe.count` that raised an ``ValueError`` if .dropna() method is invoked for single column timezone-aware values. (:issue:`13407`)
 
 Offsets
 ^^^^^^^

pandas/core/frame.py

@@ -6487,7 +6487,9 @@ def count(self, axis=0, level=None, numeric_only=False):
                 # column frames with an extension array
                 result = notna(frame).sum(axis=axis)
             else:
-                counts = notna(frame.values).sum(axis=axis)
+                # GH13407
+                series_counts = notna(frame).sum(axis=axis)
+                counts = series_counts.values
                 result = Series(counts, index=frame._get_agg_axis(axis))
 
         return result.astype('int64')

pandas/tests/frame/test_missing.py

@@ -8,6 +8,9 @@
 from numpy import nan, random
 import numpy as np
 
+import datetime
+import dateutil
+
 from pandas.compat import lrange
 from pandas import (DataFrame, Series, Timestamp,
                     date_range, Categorical)
@@ -183,6 +186,33 @@ def test_dropna_multiple_axes(self):
         inp.dropna(how='all', axis=(0, 1), inplace=True)
         assert_frame_equal(inp, expected)
 
+    def test_dropna_tz_aware_datetime(self):
+        # GH13407
+        # Example reported by GH13407
+        df = DataFrame()
+        df['Time'] = [datetime.datetime(
+            2015, 1, 1, tzinfo=dateutil.tz.tzutc())]
+        result = df.dropna(axis=0)
+        expected = DataFrame({'Time': [datetime.datetime(
+            2015, 1, 1, tzinfo=dateutil.tz.tzutc())]})
+        assert_frame_equal(result, expected)
+
+        # Ex2
+        df2 = DataFrame({'Time': [datetime.datetime(
+            2015, 1, 1, tzinfo=dateutil.tz.tzutc()),
+            None,
+            np.nan,
+            datetime.datetime(2015, 2, 2,
+                tzinfo=dateutil.tz.tzutc())]})
+        result2 = df2.dropna(axis=0)
+        expected2 = DataFrame([datetime.datetime(
+            2015, 1, 1, tzinfo=dateutil.tz.tzutc()),
+            datetime.datetime(2015, 2, 2,
+                tzinfo=dateutil.tz.tzutc())],
+            columns=['Time'],
+            index=[0, 3])
+        assert_frame_equal(result2, expected2)
+
     def test_fillna(self):
         tf = self.tsframe
         tf.loc[tf.index[:5], 'A'] = nan